Autonomous Integrity Monitoring for Vehicular Navigation With Cellular Signals of Opportunity and an IMU
Autonomous Integrity Monitoring for Vehicular Navigation With Cellular Signals of Opportunity and an IMU
复制标题
DOI：
10.1109/tits.2021.3055200
复制
发表时间：
2022-06
影响因子：
8.5
通讯作者：
Mahdi Maaref;Z. Kassas
中科院分区：
文献类型：
--
作者：
Mahdi Maaref;Z. Kassas
提出了一种利用环境蜂窝信号和惯性测量单元进行地面车辆导航的接收机自主完好性监测框架。所提出的框架占两种类型的错误，损害导航解决方案的完整性：（i）多路径和（ii）未建模的偏差，由于视线（LOS）信号阻塞和高信号衰减的蜂窝伪距测量。本文首先分析了蜂窝导航系统中的多径特性。接下来，开发了一种用于基于蜂窝的导航框架的故障检测和排除技术。仿真和实验结果与真实的长期演进（LTE）的信号，提出了评估的有效性，提出了基于RAIM的故障检测和排除技术的地面车辆导航在城市深处的环境中，在没有全球导航卫星系统（GNSS）信号。在城市环境中行驶825 m的地面车辆上的实验结果表明，所提出的基于RAIM的测量排除技术使位置均方根误差（RMSE）降低了66%。
A receiver autonomous integrity monitoring (RAIM) framework for ground vehicle navigation using ambient cellular signals of opportunity (SOPs) and an inertial measurement unit (IMU) is developed. The proposed framework accounts for two types of errors that compromise the integrity of the navigation solution: (i) multipath and (ii) unmodeled biases in the cellular pseudorange measurements due to line-of-sight (LOS) signal blockage and high signal attenuation. This paper, first, characterizes the multipath in a cellular-based navigation framework. Next, a fault detection and exclusion technique for a cellular-based navigation framework is developed. Simulation and experimental results with real long-term evolution (LTE) signals are presented evaluating the efficacy of the proposed RAIM-based fault detection and exclusion technique on a ground vehicle navigating in a deep urban environment in the absence of global navigation satellite system (GNSS) signals. The experimental results on a ground vehicle traversing 825 m in an urban environment show that the proposed RAIM-based measurement exclusion technique reduces the position root mean-squared error (RMSE) by 66%.